Location: United States – Remote Employment Type: Full-Time and Contract
We are seeking an experienced and highly technical Data Scientist to join our customer-facing consulting team. This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.Key Responsibilities
● Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions.
● Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences.
● Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models.
● Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands-on experience with technologies like Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.
● Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems.
● Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark).
● Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities.
● Ensure all client engagements and training activities are properly documented and reported via designated partner platforms.
Required Qualifications
● 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment.
● 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.
● Excellent verbal and written communication skills for effective client and internal team interaction.
● Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices.
● Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.
● Deep understanding of programming for data-intensive and scalable ML applications.
● Proven experience in deploying and managing Generative AI and NLP solutions for client applications.
Preferred Qualifications
● Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.
● Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.
● Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.
Requirements
● Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.
● Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.
Required Qualifications
● 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment.
● 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.
● Excellent verbal and written communication skills for effective client and internal team interaction.
● Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices.
● Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.
● Deep understanding of programming for data-intensive and scalable ML applications.
● Proven experience in deploying and managing Generative AI and NLP solutions for client applications.
Preferred Qualifications
● Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.
● Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.
● Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.
● Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.
● Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.
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